SEO AI Assistant

# App SEO AI Application for SEO automation and AI-powered optimization with Google Ads Keyword Planner integration. ## Features - Keyword research using Google Ads API - SERP analysis - Competitor analysis - SEO recommendations - MCP (Model Context Protocol) integration for AI assistants ## Prerequisites - Node.js (v14 or higher) - npm or yarn - Google Ads account with API access - Google Cloud Platform project with Google Ads API enabled ## Setup ### 1. Clone the repository ```bash git clone https://github.com/ccnn2509/app-seo-ai.git cd app-seo-ai ``` ### 2. Install dependencies ```bash npm install ``` ### 3. Configure environment variables Copy the example environment file: ```bash cp .env.example .env ``` Edit the `.env` file and fill in your Google Ads API credentials: ``` # Server Configuration PORT=3000 NODE_ENV=development # Google Ads API Configuration GOOGLE_ADS_DEVELOPER_TOKEN=your_developer_token GOOGLE_ADS_CLIENT_ID=your_client_id GOOGLE_ADS_CLIENT_SECRET=your_client_secret GOOGLE_ADS_REFRESH_TOKEN=your_refresh_token GOOGLE_ADS_LOGIN_CUSTOMER_ID=your_customer_id_without_dashes # SERP API Configuration (optional) SERP_API_KEY=your_serp_api_key ``` ### 4. Get Google Ads API refresh token Run the following command to get a refresh token: ```bash npm run get-token ``` This will open your browser and guide you through the OAuth2 authentication process. The refresh token will be automatically saved to your `.env` file. ### 5. Start the server For development: ```bash npm run dev ``` For production: ```bash npm start ``` The server will start on the port specified in your `.env` file (default: 3000). ## API Documentation API documentation is available at `/api-docs` when the server is running: ``` http://localhost:3000/api-docs ``` ## MCP Integration This project includes MCP (Model Context Protocol) integration, allowing AI assistants to use the API. The MCP configuration is in the `mcp.json` file. To use this with Smithery: 1. Go to [Smithery](https://smithery.ai/) 2. Create a new MCP server 3. Select the `app-seo-ai` repository 4. Configure the server settings 5. Deploy the server ## Available MCP Tools - `research_keywords` - Research keywords related to a given topic or seed keyword - `analyze_serp` - Analyze a SERP (Search Engine Results Page) for a given query - `analyze_competitors` - Analyze competitors for a given keyword or domain - `_health` - Health check endpoint ## Example Usage ### Research Keywords ```javascript // Example request to research keywords fetch('http://localhost:3000/api/keywords/ideas?keyword=seo%20tools&language=en') .then(response => response.json()) .then(data => console.log(data)); ``` ### Analyze SERP ```javascript // Example request to analyze SERP fetch('http://localhost:3000/api/serp/analyze?query=best%20seo%20tools&location=United%20States') .then(response => response.json()) .then(data => console.log(data)); ``` ### Analyze Competitors ```javascript // Example request to analyze competitors fetch('http://localhost:3000/api/competitors/analyze?domain=example.com') .then(response => response.json()) .then(data => console.log(data)); ``` ## License MIT